Apart form using PCA to reduce the dimensionality on the dataset, Elastic Net [1]} algorithm was also used for variable selection, and coefficient estimation for highly correlated features. Elastic net is a penalized regression method, which linearly combines both \(L_1\)  and \(L_2\)  penalties of the Lasso [2]} and Ridge [3]} methods. The estimator from elastic net is given by:
\(\hat{\beta }=\arg min (\frac{1}{2n}|| Y-X\beta ||_2^2+\lambda \alpha |\beta |+\frac{1}{2}\lambda (1-\alpha ) ||\beta _2||_2^2)\) 
